Using the ER model for bigger data creates a lot of complexity while designing a database model, So in order to minimize the complexity Generalization, Specialization, and Aggregation were introduced in the ER model and these were used for data abstraction in which an abstraction mechanism is used to hide details of a set of objects. Some of the terms were added to the Enhanced ER Model, where some new concepts were added. These new concepts are:
Generalization is the process of extracting common properties from a set of entities and creating a generalized entity from it. It is a bottom-up approach in which two or more entities can be generalized to a higher-level entity if they have some attributes in common. For Example, STUDENT and FACULTY can be generalized to a higher-level entity called PERSON as shown in Figure 1. In this case, common attributes like P_NAME, and P_ADD become part of a higher entity (PERSON), and specialized attributes like S_FEE become part of a specialized entity (STUDENT).
Generalization is also called as ‘ Bottom-up approach”.
In specialization, an entity is divided into sub-entities based on its characteristics. It is a top-down approach where the higher-level entity is specialized into two or more lower-level entities. For Example, an EMPLOYEE entity in an Employee management system can be specialized into DEVELOPER, TESTER, etc. as shown in Figure 2. In this case, common attributes like E_NAME, E_SAL, etc. become part of a higher entity (EMPLOYEE), and specialized attributes like TES_TYPE become part of a specialized entity (TESTER).
Specialization is also called as ” Top-Down approch”.
Inheritance: It is an important feature of generalization and specialization
- Attribute inheritance: allows lower level entities to inherit the attributes of higher level entities and vice versa.
- in diagram: Car entity is an inheritance of Vehicle entity ,So Car can acquire attributes of Vehicle example:car can acquire Model attribute of Vehicle.
example of Attribute Inheritance
- Participation inheritance: In participation inheritance, relationships involving higher level entity set also inherited by lower level entity and vice versa.
- in diagram: Vehicle entity has an relationship with Cycle entity ,So Cycle entity can acquire attributes of lower level entities i.e Car and Bus since it is inheritance of Vehicle.
Example of Participation Inheritance
An ER diagram is not capable of representing the relationship between an entity and a relationship which may be required in some scenarios. In those cases, a relationship with its corresponding entities is aggregated into a higher-level entity. Aggregation is an abstraction through which we can represent relationships as higher-level entity sets.
For Example, an Employee working on a project may require some machinery. So, REQUIRE relationship is needed between the relationship WORKS_FOR and entity MACHINERY. Using aggregation, WORKS_FOR relationship with its entities EMPLOYEE and PROJECT is aggregated into a single entity and relationship REQUIRE is created between the aggregated entity and MACHINERY.
Representing Aggregation Via Schema
To represent aggregation, create a schema containing the following things.
- the primary key to the aggregated relationship
- the primary key to the associated entity set
- descriptive attribute, if exists
FAQs on Generalization, Specialization and Aggregation in ER Model
Q.1: What are Generalization, Specialization, and Aggregation in ER Model?
Generalization is the higher level of understanding of data from lower levels of data whereas Specialization is the process of defining one or more entities from present entities and Aggregation is the process of combining two or more entities.
Q.2: What is the purpose of the Generalization?
Generalization is simply gathering the common properties from entities and creating a generalized concept from those extracted data. Generalization helps in improving the flexibility, and reusability of the database.
Q.3: Why is generalization important in the database?
Generalization is important in the database because it helps to gather important information so that it becomes easier and faster for the user the analysis of data and it also helps in making decisions faster.
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